- paper/pnas -> paper/manuscript (venue-neutral)
- configs/layer1 -> configs/inheritance, src/knowledge -> src/inheritance
(imported as `inheritance`), make layer1 -> make inheritance; layer2 alias dropped
- inheritance and trained-network bundles named after the manuscript figure
they feed (fig2_grounding_sweep, figS3_rebaselining, ...), or descriptively
where they feed none; configs keep their `experiment:` value so parquet
hashes are unchanged, only output.dir moves
- figure scripts, SI figure sources, notebooks, REPRODUCING.md, README and the
SI Methods/tables updated; make clean no longer deletes tracked manifests;
reproduce.sh hashes the s{seed}/ layouts too
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
An audit of the figure pipeline found real sync gaps, now closed:
- `paper/pnas/make_figs.py` (which draws every manuscript figure) was invoked
by NO Makefile target or script - a manual step. Added `make paper-figures`.
- `configs/llm/epistasis{,_compat}.yaml` were reachable from nothing at all,
despite producing Fig. 3C-D. Added `make llm-epistasis` (+ its statistics).
- `make figures` never regenerated the MNIST montage that Fig. 2B embeds;
it now runs with the `mnist` target (it needs torch - it re-simulates).
- Added `make llm-society`, `env-notebooks`, `notebooks`.
New REPRODUCING.md is the authoritative map: every manuscript panel -> the
artifact it plots -> the config that produced it -> that config's seed, plus
the determinism policy (biological tier bitwise; GPU tiers statistical), the
seed-provenance statement, and an artifact-hash verification snippet. All 44
committed bundles currently hash-match their manifests, and figure
regeneration is pixel-identical (verified by comparison).
reproduce.sh delivers the one-command reproduction the paper's Methods
promises, writing REPRODUCED.md with recomputed hashes per bundle.
Two executed notebooks: 01 builds the Wright-Fisher model from scratch and
checks both closed forms interactively (runs in ~1 min on a laptop); 02
verifies artifact hashes then regenerates and displays all seven manuscript
figures. Both execute end-to-end (`make notebooks`).
Also pins `.python-version` to 3.14: the interpreter was previously
unpinned, and a `uv sync` silently switched it to 3.11 mid-session (see
tasks/lessons.md). README rewritten - it still described a Layer-1-only repo
of E1-E6 and pointed at a figure_manifest.md that does not exist.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
The paper's key move drawn as a two-panel partner to the programme grid (now
Fig. 1A): on the left, the usual picture — contemporaries exchanging messages
(multi-agent systems, one moment on the clock); on the right, the same
ecosystem seen along its time axis — a pedigree in which a rare capability
(gold dot) is lost under single-parent inheritance, reassembled by merging
complementary parents, and re-supplied by grounding from a reality that can
say no (the globe). Friendly-robot glyphs, colour-coded capability dots;
build.py now stacks multiple PDFs per figure; the Introduction cites 1A and
1B in panel order.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
Replaces the results table with a pipeline figure: five questions x three
architecture tiers (exact Wright-Fisher simulator, trained networks, language
models), filled cells naming the experiments, dashed cells the honest gaps.
Table 1 (the dictionary) stays; Table 2 moves to SI Appendix Table S2. The
renumber surfaced a pre-existing citation-order violation (the LLM figure was
cited in the recombination section before Figs. 3-6), so figures are renumbered
to strict first-citation order (LLM tier is now Fig. 3). Fig. 2B: the montage's
baked-in raster labels are cropped away and replaced with vector row numbers
under a rotated "generation" header.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
